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Problematic Online Behaviors Among Gamers: the Links Between Problematic Gaming, Gambling, Shopping, Pornography Use, and Social Networking

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Abstract

The aim of the current study was to investigate how problematic online gaming, problematic online gambling, problematic online shopping, problematic online pornography use, and problematic online social networking are associated with each other in bivariate and multivariate, network analytic analyses in an international gamer population. The effective sample comprised 4,416 gamers (age M = 23.31, SD = 6.72; 94% male). Participants filled out the specific problematic Internet use scales on gaming, gambling, shopping, pornography, and social networking. The results showed that problematic online gaming yielded small-to-medium positive bivariate correlations with other problematic behaviors. However, the exploratory graph analysis showed that all Internet-based problematic behaviors were separate entities. Finally, problematic online gaming yielded the highest scores, followed by problematic online social networking, gambling, and pornography. While gaming was the most prevalent Internet-based problematic behavior among gamers, the results further suggested that the other Internet-based problematic behaviors investigated may co-occur despite being considered separate entities.

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References

  • American Psychiatric Association. (2013). Diagnostic and statistical manual of mental disorders (DSM-5®). (5th ed.). American Psychiatric Association Publishing.

  • Baggio, S., Starcevic, V., Studer, J., Simon, O., Gainsbury, S. M., Gmel, G., & Billieux, J. (2018). Technology-mediated addictive behaviors constitute a spectrum of related yet distinct conditions: A network perspective. Psychology of Addictive Behaviors, 32(5), 564–572. https://doi.org/10.1037/adb0000379

    Article  Google Scholar 

  • Baker, D. A., & Algorta, G. P. (2016). The relationship between online social networking and depression: A systematic review of quantitative studies. Cyberpsychology, Behavior, and Social Networking, 19(11), 638–648. https://doi.org/10.1089/cyber.2016.0206

    Article  Google Scholar 

  • Barrault, S., & Varescon, I. (2013). Cognitive distortions, anxiety, and depression among regular and pathological gambling online poker players. Cyberpsychology, Behavior, and Social Networking, 16(3), 183–188. https://doi.org/10.1089/cyber.2012.0150

    Article  Google Scholar 

  • Montag, C., & Becker, B. (2019). Psychological and neuroscientific advances to understand internet use disorder. Neuroforum, 25(2), 99–107. https://doi.org/10.1515/nf-2018-0026

    Article  Google Scholar 

  • Bonnaire, C., & Baptista, D. (2019). Internet Gaming Disorder in male and female young adults: The role of alexithymia, depression, anxiety and gaming type. Psychiatry Research, 272, 521–530. https://doi.org/10.1016/j.psychres.2018.12.158

    Article  Google Scholar 

  • Borgogna, N. C., Duncan, J., & McDermott, R. C. (2018). Is scrupulosity behind the relationship between problematic pornography viewing and depression, anxiety, and stress? Sexual Addiction & Compulsivity, 25(4), 293–318. https://doi.org/10.1080/10720162.2019.1567410

    Article  Google Scholar 

  • Borsboom, D., & Cramer, A. O. J. (2013). Network analysis: An integrative approach to the structure of psychopathology. Annual Review of Clinical Psychology, 9(1), 91–121. https://doi.org/10.1146/annurev-clinpsy-050212-185608

    Article  Google Scholar 

  • Brand, M., Wegmann, E., Stark, R., Muller, A., Wolfling, K., Robbins, T. W., & Potenza, M. N. (2019). The Interaction of Person-Affect-Cognition-Execution (I-PACE) model for addictive behaviors: Update, generalization to addictive behaviors beyond internet-use disorders, and specification of the process character of addictive behaviors. Neuroscience & Biobehavioral Reviews, 104, 1–10. https://doi.org/10.1016/j.neubiorev.2019.06.032

    Article  Google Scholar 

  • Brand, M., Young, K. S., Laier, C., Wölfling, K., & Potenza, M. N. (2016). Integrating psychological and neurobiological considerations regarding the development and maintenance of specific Internet-use disorders: An Interaction of Person-Affect-Cognition-Execution (I-PACE) model. Neuroscience & Biobehavioral Reviews, 71, 252–266. https://doi.org/10.1016/j.neubiorev.2016.08.033

    Article  Google Scholar 

  • Christensen, A. P. (2020). Towards a network psychometrics approach to assessment: Simulations for redundancy, dimensionality, and loadings [Unpublished doctoral dissertation, University of North Carolina at Greensboro]. https://doi.org/10.31234/osf.io/84kgd

  • Christensen, A. P., & Golino, H. (2019). Estimating the stability of the number of factors via Bootstrap Exploratory Graph Analysis: A tutorial [Preprint]. PsyArXiv. https://doi.org/10.31234/osf.io/9deay

  • Christensen, A.P., Golino, H. (2021). On the equivalency of factor and network loadings. Behavior Research Methods. https://doi.org/10.3758/s13428-020-01500-6

  • Claes, L., Müller, A., & Luyckx, K. (2016). Compulsive buying and hoarding as identity substitutes: The role of materialistic value endorsement and depression. Comprehensive Psychiatry, 68, 65–71. https://doi.org/10.1016/j.comppsych.2016.04.005

    Article  Google Scholar 

  • Cohen, J. (1988). Statistical power analysis for the behavioral sciences. L. Erlbaum Associates. https://doi.org/10.4324/9780203771587

  • Cohen, J. (1992). A power primer. Psychological Bulletin, 112(1), 155–159. https://doi.org/10.1037/0033-2909.112.1.155

    Article  CAS  Google Scholar 

  • Cudo, A., Torój, M., Misiuro, T., & Griffiths, M. D. (2020). Problematic Facebook use and problematic video gaming among female and male gamers. Cyberpsychology, Behavior, and Social Networking, 23(2), 126–133. https://doi.org/10.1089/cyber.2019.0252

    Article  Google Scholar 

  • Davis, R. (2001). A cognitive-behavioral model of pathological internet use. Computers in Human Behavior, 17, 187–195.

    Article  Google Scholar 

  • Elhai, J. D., Dvorak, R. D., Levine, J. C., & Hall, B. J. (2017). Problematic smartphone use: A conceptual overview and systematic review of relations with anxiety and depression psychopathology. Journal of Affective Disorders, 207, 251–259. https://doi.org/10.1016/j.jad.2016.08.030

    Article  Google Scholar 

  • Elhai, J. D., Sapci, O., Yang, H., Amialchuk, A., Rozgonjuk, D., & Montag, C. (2021). Objectively-measured and self-reported smartphone use in relation to surface learning, procrastination, academic productivity, and psychopathology symptoms in college students. Human Behavior and Emerging Technologies, hbe2.254. https://doi.org/10.1002/hbe2.254

  • Epskamp, S., Borsboom, D., & Fried, E. I. (2018a). Estimating psychological networks and their accuracy: A tutorial paper. Behavior Research Methods, 50(1), 195–212. https://doi.org/10.3758/s13428-017-0862-1

    Article  Google Scholar 

  • Epskamp, S., Cramer, A. O., Waldorp, L. J., Schmittmann, V. D., & Borsboom, D. (2012). qgraph: Network visualizations of relationships in psychometric data. Journal of Statistical Software, 48(4), 1–18.

    Article  Google Scholar 

  • Epskamp, S., Waldorp, L. J., Mõttus, R., & Borsboom, D. (2018b). The Gaussian graphical model in cross-sectional and time-series data. Multivariate Behavioral Research, 53(4), 453–480. https://doi.org/10.1080/00273171.2018.1454823

    Article  Google Scholar 

  • Golino, H. F., & Christensen, A. P. (2020). EGAnet: exploratory graph analysis—A framework for estimating the number of dimensions in multivariate data using network psychometrics (0.9.5) [Computer software].

  • Golino, H. F., & Epskamp, S. (2017). Exploratory graph analysis: A new approach for estimating the number of dimensions in psychological research. PLoS ONE, 12(6), e0174035. https://doi.org/10.1371/journal.pone.0174035

    Article  CAS  Google Scholar 

  • Griffiths, M. D. (1996). Internet ‘addiction’: An issue for clinical psychology? Clinical Psychology Forum, 97, 32–36.

    Article  Google Scholar 

  • Griffiths, M. D. (1999). Internet addiction: Internet fuels other addictions. Student British Medical Journal, 7, 428–429.

    Google Scholar 

  • Griffiths, M. D. (2000). Internet addiction—Time to be taken seriously? Addiction Research, 8(5), 413–418. https://doi.org/10.3109/16066350009005587

    Article  Google Scholar 

  • Griffiths, M. D., & Pontes, H. M. (2014). Internet addiction disorder and Internet Gaming Disorder are not the same. Journal of Addiction Research & Therapy, 05(04). https://doi.org/10.4172/2155-6105.1000e124

  • Griffiths, M. D., & Szabo, A. (2014). Is excessive online usage a function of medium or activity?: An empirical pilot study. Journal of Behavioral Addictions, 3(1), 74–77. https://doi.org/10.1556/JBA.2.2013.016

    Article  Google Scholar 

  • Hothorn, T., Bretz, F., & Westfall, P. (2008). Simultaneous inference in general parametric models. Biometrical Journal, 50(3), 346–363.

    Article  Google Scholar 

  • Hussain, Z., Griffiths, M. D., & Sheffield, D. (2017). An investigation into problematic smartphone use: The role of narcissism, anxiety, and personality factors. Journal of Behavioral Addictions, 6(3), 378–386. https://doi.org/10.1556/2006.6.2017.052

    Article  Google Scholar 

  • Kardefelt-Winther, D. (2014). A conceptual and methodological critique of internet addiction research: Towards a model of compensatory internet use. Computers in Human Behavior, 31, 351–354. https://doi.org/10.1016/j.chb.2013.10.059

    Article  Google Scholar 

  • Kim, Y., Jeong, J. E., Cho, H., Jung, D. J., Kwak, M., Rho, M. J., Yu, H., Kim, D. J., & Choi, I. Y. (2016). Personality factors predicting smartphone addiction predisposition: Behavioral inhibition and activation systems, impulsivity, and self-control. PLoS ONE, 11(8), e0159788. https://doi.org/10.1371/journal.pone.0159788

    Article  CAS  Google Scholar 

  • Kircaburun, K., Pontes, H. M., Stavropoulos, V., & Griffiths, M. D. (2020). A brief psychological overview of disordered gaming. Current Opinion in Psychology, 36, 38–43. https://doi.org/10.1016/j.copsyc.2020.03.004

    Article  Google Scholar 

  • Kuss, D. J., Pontes, H. M., & Griffiths, M. D. (2018). Neurobiological correlates in Internet Gaming Disorder: A systematic literature review. Frontiers in Psychiatry, 9, 166. https://doi.org/10.3389/fpsyt.2018.00166

  • Lakens, D. (2013). Calculating and reporting effect sizes to facilitate cumulative science: A practical primer for t-tests and ANOVAs. Frontiers in Psychology, 4. https://doi.org/10.3389/fpsyg.2013.00863

  • Lee, H. S. (2018). Two factors of overseas online shopping: Self-efficacy and impulsivit. Journal of Distribution Science, 168(79), 89. https://doi.org/10.15722/JDS.16.8.201808.79

    Article  Google Scholar 

  • Lopez-Fernandez, O., Kuss, D. J., Romo, L., Morvan, Y., Kern, L., Graziani, P., Rousseau, A., Rumpf, H. J., Bischof, A., Gassler, A. K., Schimmenti, A., Passanisi, A., Mannikko, N., Kaarianen, M., Demetrovics, Z., Kiraly, O., Choliz, M., Zacares, J. J., Serra, E., & Billieux, J. (2017). Self-reported dependence on mobile phones in young adults: A European cross-cultural empirical survey. Journal of Behavioral Addictions, 6(2), 168–177. https://doi.org/10.1556/2006.6.2017.020

    Article  Google Scholar 

  • Lowe-Calverley, E., & Pontes, H. M. (2020). Challenging the concept of smartphone addiction: An empirical pilot study of smartphone usage patterns and psychological well-being. Cyberpsychology, Behavior, and Social Networking, 23(8), 550–556. https://doi.org/10.1089/cyber.2019.0719

    Article  Google Scholar 

  • Männikkö, N., Ruotsalainen, H., Miettunen, J., Pontes, H. M., & Kääriäinen, M. (2020). Problematic gaming behaviour and health-related outcomes: A systematic review and meta-analysis. Journal of Health Psychology, 25(1), 67–81. https://doi.org/10.1177/1359105317740414

    Article  Google Scholar 

  • Marengo, D., Poletti, I., & Settanni, M. (2020). The interplay between neuroticism, extraversion, and social media addiction in young adult Facebook users: Testing the mediating role of online activity using objective data. Addictive Behaviors, 102, 106150. https://doi.org/10.1016/j.addbeh.2019.106150

    Article  Google Scholar 

  • Marmet, S., Studer, J., Wicki, M., Bertholet, N., Khazaal, Y., & Gmel, G. (2019). Unique versus shared associations between self-reported behavioral addictions and substance use disorders and mental health problems: A commonality analysis in a large sample of young Swiss men. Journal of Behavioral Addictions, 8(4), 664–677. https://doi.org/10.1556/2006.8.2019.70

    Article  Google Scholar 

  • Montag, C., Bey, K., Sha, P., Li, M., Chen, Y.-F., Liu, W.-Y., Zhu, Y.-K., Li, C.-B., Markett, S., Keiper, J., & Reuter, M. (2015). Is it meaningful to distinguish between generalized and specific Internet addiction? Evidence from a cross-cultural study from Germany, Sweden, Taiwan and China: Specific forms of Internet addiction. Asia-Pacific Psychiatry, 7(1), 20–26. https://doi.org/10.1111/appy.12122

    Article  Google Scholar 

  • Montag, C., Flierl, M., Markett, S., Walter, N., Jurkiewicz, M., & Reuter, M. (2011). Internet addiction and personality in first-person-shooter video gamers. Journal of Media Psychology, 23(4), 163–173. https://doi.org/10.1027/1864-1105/a000049

    Article  Google Scholar 

  • Montag, C., Lachmann, B., Herrlich, M., & Zweig, K. (2019a). Addictive features of social media/messenger platforms and freemium games against the background of psychological and economic theories. International Journal of Environmental Research and Public Health, 16(14), 2612. https://doi.org/10.3390/ijerph16142612

    Article  Google Scholar 

  • Montag, C., Schivinski, B., Sariyska, R., Kannen, C., Demetrovics, Z., & Pontes, H. M. (2019b). Psychopathological symptoms and gaming motives in disordered gaming—A psychometric comparison between the WHO and APA diagnostic frameworks. Journal of Clinical Medicine, 8(10), 1691. https://doi.org/10.3390/jcm8101691

    Article  Google Scholar 

  • Müller, M., Brand, M., Mies, J., Lachmann, B., Sariyska, R., & Montag, C. (2017). The 2D:4D marker and different forms of internet use disorder. Frontiers in Psychiatry, 8, 213. https://doi.org/10.3389/fpsyt.2017.00213

    Article  Google Scholar 

  • Parry, D. A., Davidson, B. I., Sewall, C. J. R., Fisher, J. T., Mieczkowski, H., & Quintana, D. S. (2021). A systematic review and meta-analysis of discrepancies between logged and self-reported digital media use. Nature Human Behaviour. https://doi.org/10.1038/s41562-021-01117-5

  • Pearcy, B. T. D., McEvoy, P. M., & Roberts, L. D. (2017). Internet Gaming Disorder explains unique variance in psychological distress and disability after controlling for comorbid depression, OCD, ADHD, and anxiety. Cyberpsychology, Behavior, and Social Networking, 20(2), 126–132. https://doi.org/10.1089/cyber.2016.0304

    Article  Google Scholar 

  • Peterka-Bonetta, J., Sindermann, C., Elhai, J. D., & Montag, C. (2019). Personality associations with smartphone and internet use disorder: A comparison study including links to impulsivity and social anxiety. Frontiers in Public Health, 7, 127. https://doi.org/10.3389/fpubh.2019.00127

    Article  Google Scholar 

  • Pinheiro, J., Bates, D., DebRoy, S., Sarkar, D., & R Core Team. (2019). nlme: Linear and nonlinear mixed effects models (3.1–143) [Computer software]. https://CRAN.R-project.org/package=nlme

  • Pontes, H. M. (2017). Investigating the differential effects of social networking site addiction and Internet Gaming Disorder on psychological health. Journal of Behavioral Addictions, 6(4), 601–610. https://doi.org/10.1556/2006.6.2017.075

    Article  Google Scholar 

  • Pontes, H. M., & Griffiths, M. D. (2020). A new era for gaming disorder research: Time to shift from consensus to consistency. Addictive Behaviors, 103, 106059. https://doi.org/10.1016/j.addbeh.2019.106059

    Article  Google Scholar 

  • Pontes, H. M., Schivinski, B., Brzozowska-Woś, M., & Stavropoulos, V. (2019a). Laxer clinical criteria for gaming disorder may hinder future efforts to devise an efficient diagnostic approach: A tree-based model study. Journal of Clinical Medicine, 8(10), 1730. https://doi.org/10.3390/jcm8101730

    Article  Google Scholar 

  • Pontes, H. M., Schivinski, B., Sindermann, C., Li, M., Becker, B., Zhou, M., & Montag, C. (2019b). Measurement and conceptualization of gaming disorder according to the World Health Organization framework: The development of the gaming disorder test. International Journal of Mental Health and Addiction. https://doi.org/10.1007/s11469-019-00088-z

    Article  Google Scholar 

  • Pontes, H. M., Szabo, A., & Griffiths, M. D. (2015). The impact of Internet-based specific activities on the perceptions of Internet addiction, quality of life, and excessive usage: A cross-sectional study. Addictive Behaviors Reports, 1, 19–25. https://doi.org/10.1016/j.abrep.2015.03.002

  • R Core Team. (2021). R: A language and environment for statistical computing (4.0.3) [Computer software]. R Core Team.

  • Rozgonjuk, D., Elhai, J. D., Täht, K., Vassil, K., Levine, J. C., & Asmundson, G. J. G. (2019a). Non-social smartphone use mediates the relationship between intolerance of uncertainty and problematic smartphone use: Evidence from a repeated-measures study. Computers in Human Behavior, 96, 56–62. https://doi.org/10.1016/j.chb.2019.02.013

    Article  Google Scholar 

  • Rozgonjuk, D., Levine, J. C., Hall, B. J., & Elhai, J. D. (2018). The association between problematic smartphone use, depression and anxiety symptom severity, and objectively measured smartphone use over one week. Computers in Human Behavior, 87, 10–17. https://doi.org/10.1016/j.chb.2018.05.019

    Article  Google Scholar 

  • Rozgonjuk, D., Pruunsild, P., Jürimäe, K., Schwarz, R.-J., & Aru, J. (2020a). Instagram use frequency is associated with problematic smartphone use, but not with depression and anxiety symptom severity. Mobile Media & Communication, 8(3), 400–418. https://doi.org/10.1177/2050157920910190

    Article  Google Scholar 

  • Rozgonjuk, D., Ryan, T., Kuljus, J. K., Täht, K., & Scott, G. G. (2019). Social comparison orientation mediates the relationship between neuroticism and passive Facebook use. Cyberpsychology: Journal of Psychosocial Research on Cyberspace, 13(1). https://doi.org/10.5817/cp2019-1-2

  • Rozgonjuk, D., Sindermann, C., Elhai, J. D., Christensen, A. P., & Montag, C. (2020b). Associations between symptoms of problematic smartphone, Facebook, WhatsApp, and Instagram use: An item-level exploratory graph analysis perspective. Journal of Behavioral Addictions, 9(3), 686–697. https://doi.org/10.1556/2006.2020.00036

    Article  Google Scholar 

  • Şalvarlı, S. I., & Griffiths, D. (2019). Internet Gaming Disorder and its associated personality traits: A systematic review using PRISMA guidelines. International Journal of Mental Health and Addiction. https://doi.org/10.1007/s11469-019-00081-6

  • Sawilowsky, S. S. (2009). New effect size rules of thumb. Journal of Modern Applied Statistical Methods, 8(2), 597–599. https://doi.org/10.22237/jmasm/1257035100

  • Schivinski, B., Brzozowska-Woś, M., Buchanan, E. M., Griffiths, M. D., & Pontes, H. M. (2018). Psychometric assessment of the Internet Gaming Disorder diagnostic criteria: An Item Response Theory study. Addictive Behaviors Reports, 8, 176–184. https://doi.org/10.1016/j.abrep.2018.06.004

    Article  Google Scholar 

  • Shapira, N. A., Goldsmith, T. D., Keck, P. E., Jr., Khosla, U. M., & McElroy, S. L. (2000). Psychiatric features of individuals with problematic internet use. Journal of Affective Disorders, 57(1–3), 267–272. https://doi.org/10.1016/S0165-0327(99)00107-X

    Article  CAS  Google Scholar 

  • Starcevic, V. (2013). Is Internet addiction a useful concept? Australian & New Zealand Journal of Psychiatry, 47(1), 16–19. https://doi.org/10.1177/0004867412461693

    Article  Google Scholar 

  • Stavropoulos, V., Adams, B. L. M., Beard, C. L., Dumble, E., Trawley, S., Gomez, R., & Pontes, H. M. (2019). Associations between attention deficit hyperactivity and Internet Gaming Disorder symptoms: Is there consistency across types of symptoms, gender and countries? Addictive Behaviors Reports, 9, 100158. https://doi.org/10.1016/j.abrep.2018.100158

    Article  Google Scholar 

  • Trivedi, R. H., & Teichert, T. (2018). Attitudes, beliefs and impulsivity in online gambling addiction. International Gambling Studies, 18(2), 327–342. https://doi.org/10.1080/14459795.2018.1466188

    Article  Google Scholar 

  • Wartberg, L., Kriston, L., & Thomasius, R. (2020). Internet Gaming Disorder and problematic social media use in a representative sample of German adolescents: Prevalence estimates, comorbid depressive symptoms and related psychosocial aspects. Computers in Human Behavior, 103, 31–36. https://doi.org/10.1016/j.chb.2019.09.014

    Article  Google Scholar 

  • Wegmann, E., Müller, S. M., Ostendorf, S., & Brand, M. (2018). Highlighting internet-communication disorder as further internet-use disorder when considering neuroimaging studies. Current Behavioral Neuroscience Reports, 5(4), 295–301. https://doi.org/10.1007/s40473-018-0164-7

    Article  Google Scholar 

  • Wéry, A., Deleuze, J., Canale, N., & Billieux, J. (2018). Emotionally laden impulsivity interacts with affect in predicting addictive use of online sexual activity in men. Comprehensive Psychiatry, 80, 192–201. https://doi.org/10.1016/j.comppsych.2017.10.004

    Article  Google Scholar 

  • Wickham, H. (2009). ggplot2: Elegant graphics for data analysis. Springer-Verlag.

  • Wong, H. Y., Mo, H. Y., Potenza, M. N., Chan, M. N. M., Lau, W. M., Chui, T. K., Pakpour, A. H., & Lin, C.-Y. (2020). Relationships between severity of internet gaming disorder, severity of problematic social media use, sleep quality and psychological distress. International Journal of Environmental Research and Public Health, 17(6), 1879. https://doi.org/10.3390/ijerph17061879

    Article  Google Scholar 

  • World Health Organization. (2018a). Gaming disorder. https://www.who.int/news-room/q-a-detail/gaming-disorder. Accessed on 23.07.2021.

  • World Health Organization. (2018b). International classification of diseases and related health problems (11th ed.). World Health Organization. https://icd.who.int/browse11/l-m/en#/http://id.who.int/icd/entity/1448597234

  • Young, K. S. (1996). Psychology of computer use: XL. Addictive use of the Internet: A case that breaks the stereotype. Psychological Reports, 79(3), 899–902. https://doi.org/10.2466/pr0.1996.79.3.899

  • Young, K. S. (1998). Internet addiction: The emergence of a new clinical disorder. CyberPsychology & Behavior, 1(3), 237–244. https://doi.org/10.1089/cpb.1998.1.237

    Article  Google Scholar 

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Authors and Affiliations

  1. Department of Molecular Psychology, Institute of Psychology and Education, Ulm University, Helmholtzstraße 8/1, 89081, Ulm, Germany

    Dmitri Rozgonjuk & Christian Montag

  2. Institute of Mathematics and Statistics, University of Tartu, Tartu, Estonia

    Dmitri Rozgonjuk

  3. School of Media and Communication, RMIT University, Melbourne, Australia

    Bruno Schivinski

  4. Department of Organizational Psychology, University of London, London, UK

    Bruno Schivinski & Halley M. Pontes

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  1. Dmitri Rozgonjuk
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  2. Bruno Schivinski
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  4. Christian Montag
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Contributions

Conceptualization: DR and CM; Data collection: HMP, BS, CM; Analysis: DR; First manuscript draft: DR; Review and editing: BS, HMP, CM.

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Correspondence to Dmitri Rozgonjuk.

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The study project was approved by the Institutional Review Board of Ulm University.

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None. But for reasons of transparency the authors mention that the present study was part of the ESL Smart Gaming Campaign. While ESL supported the present study by presenting information about it on their website, this organization had no direct or indirect role in the present study. The present study was conducted entirely independently, and ESL did not provide financial support to this research.

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The original version of this article was revised: The third sentence of the second paragraph in the Sample and Procedure section should have read as follows: The study has received ethical approval by the research team's University Ethics Committee (College Research Ethics Committee of the Nottingham Trent University [2018/95]).

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Rozgonjuk, D., Schivinski, B., Pontes, H.M. et al. Problematic Online Behaviors Among Gamers: the Links Between Problematic Gaming, Gambling, Shopping, Pornography Use, and Social Networking. Int J Ment Health Addiction 21, 240–257 (2023). https://doi.org/10.1007/s11469-021-00590-3

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